Introduces the compact genetic algorithm (cGA) which represents the population as a probability distribution over the set of solutions and is operationally equivalent to the order-one behavior of the simple GA with uniform crossover.Expand

Learning Gene Linkage to E ciently Solve Problems of Bounded Di culty Using Genetic Algorithms by Georges Raif Harik Co-Chairs: Keki B. Irani and David E. Goldberg The complicated nature of modern… Expand

The paper presents a model for predicting the convergence quality of genetic algorithms that incorporates previous knowledge about decision making in genetic algorithms.Expand

Blended learning is a powerful training strategy and approach for any organization seeking to optimize building employee skills and competencies with less time away from the job and lower travel costs.Expand

This chapter explores the relationship between the linkage-learning problem and that of learning probability distributions over multi-variate spaces.Expand

Consider a gambler who starts with an initial fortune of $1 and then on each successive gamble either wins $1 or loses $1 independent of the past with probabilities p and q = 1−p respectively.Expand